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Crime Pattern Detection Using Data Mining

  • Can crimes be modeled as data mining problems? We will try to answer this question in this paper. Crimes are a social nuisance and cost our society dearly in several ways. Any research that can help in solving crimes faster will pay for itself. Here we look at use of clustering algorithm for a data mining approach to help detect the crimes patterns and speed up the process of solving crime. We will look at k-means clustering with some enhancements to aid in the process of identification of crime patterns. We will apply these techniques to real crime data from a sheriff’s office and validate our results. We also use semi-supervised learning technique here for knowledge discovery from the crime records and to help increase the predictive accuracy. We also developed a weighting scheme for attributes here to deal with limitations of various out of the box clustering tools and techniques. This easy to implement machine learning framework works with the geo-spatial plot of crime and helps to improve the productivity of the detectives and other law enforcement officers. It can also be applied for counter terrorism for homeland security.

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Metadaten
Author:Shyam Varan Nath
URN:https://nbn-resolving.org/urn:nbn:de:gbv:hil2-opus-543
Document Type:Conference Proceeding
Language:English
Date of Publication (online):2011/04/28
Contributing Corporation:Florida Atlantic University/ Oracle Corporation
Release Date:2011/04/28
Tag:clustering; data mining; k-means; law-enforcement; semi-supervised learning
Source:LWA 2006: Lernen - Wissensentdeckung - Adaptivität, Hildesheim, 9. - 11. Oktober 2006
PPN:Link zum Katalog
Contributor:Althoff, Klaus-Dieter
Institutes:Fachbereich IV / Informatik
DDC classes:000 Allgemeines, Informatik, Informationswissenschaft / 000 Allgemeines, Wissenschaft / 004 Informatik
Licence (German):License LogoDeutsches Urheberrecht